Analisis Sentimen Terhadap Pemain Diaspora Timnas Indonesia Pada Media Sosial Instagram Menggunankan Metode Support Vector Machine (Svm)

Ramadani, Sendi (2024) Analisis Sentimen Terhadap Pemain Diaspora Timnas Indonesia Pada Media Sosial Instagram Menggunankan Metode Support Vector Machine (Svm). S1 Sistem Informasi thesis, STMIK Widya Cipta Dharma.

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Abstract

Sendi Ramadani, 2024, Anlaisis Sentimen Terhadap Pemain Diaspora Timnas Indonesia Pada media Sosial Instagram Menggunakan Metode Suppurt Vector Machine (SVM), Sekolah Tinggi Manajemen Informastika Dan Komputer Widya Cipta Dharma, Pembimbing (I) Drs.Azahari.,M.Kom, Pembimbing (II) H.Tommy Bustomi., S.Kom., M.Kom Kata Kunci : Analisis Sentimen, Support Vector Machine, Pemain Diaspora, Tim Nasional Indonesia, Instagram Penelitian ini bertujuan untuk menganalisis sentimen terhadap pemain diaspora Tim Nasional Indonesia di platform media sosial Instagram menggunakan metode Support Vector Machine (SVM). Pemain diaspora sering menjadi sorotan publik dan media sosial sebagai sarana interaksi langsung dengan penggemar. Oleh karena itu, pemahaman terhadap sentimen publik terhadap mereka menjadi penting untuk membangun hubungan yang lebih baik antara pemain dan penggemar. Penelitian ini mengumpulkan data dari unggahan dan komentar di akun Instagram resmi serta akun-akun media sosial terkait pemain diaspora. Data tersebut kemudian diproses melalui teknik praproses teks tokenisasi, penghilangan stopwords, dan stemming. Fitur-fitur dari teks dipilih dan diekstraksi untuk melatih model SVM, yang merupakan metode machine learning populer dalam klasifikasi teks. Hasil dari penelitian ini menunjukkan sentimen yang dominan, netral dibandingkan dengan sentimen positif maupun negatif, serta menunjukkan bahwa metode Support Vector Machine mampu mengklasifikasikan sentimen dengan tingkat akurasi sebesar 82%, presisi sebesar 81%, dan recall sebesar 80%. dan Penelitian ini bertujuan untuk berkontribusi pada pengembangan metode analisis sentimen yang lebih canggih dan efektif serta memberikan dasar bagi penelitian lebih lanjut dalam memahami dinamika opini publik dalam konteks politik modern yang semakin kompleks ============================================================ Sendi Ramadani, 2024, Sentiment Analysis of Indonesian National Team Diaspora Players on Instagram Social Media Using Support Vector Machine (SVM) Method, Widya Cipta Dharma School of Informatics and Computer Management, Supervisor (I) Drs. Azahari., M.Kom, Supervisor (II) H. Tommy Bustomi., S.Kom., M.Kom Keywords: Sentiment Analysis, Support Vector Machine, Diaspora Players, Indonesian National Team, Instagram This study aims to analyze sentiment towards diaspora players of the Indonesian National Team on the social media platform Instagram using the Support Vector Machine (SVM) method. Diaspora players often become the focus of public attention, and social media serves as a direct interaction platform with fans. Therefore, understanding public sentiment towards them is crucial for building better relationships between players and fans. This research collects data from posts and comments on the official Instagram account as well as social media accounts related to diaspora players. The data is then processed through text preprocessing techniques such as tokenization, stopword removal, and stemming. Text features are selected and extracted to train the SVM model, which is a popular machine learning method for text classification. The results of this study show that the dominant sentiment is neutral compared to positive or negative sentiments, and demonstrate that the Support Vector Machine method can classify sentiment with an accuracy rate of 82%, precision of 81%, and recall of 80%. This research aims to contribute to the development of more sophisticated and effective sentiment analysis methods and provide a foundation for further research in understanding the dynamics of public opinion in the increasingly complex context of modern politics.

Item Type: Thesis (S1 Sistem Informasi)
Additional Information: Pembimbing 1 : Drs. Azahari, M.Kom pembimbing 2 : H. Tommy Bustomi, S.Kom., M.Kom
Uncontrolled Keywords: Analisis Sentimen, Support Vector Machine, Pemain Diaspora, Tim Nasional Indonesia, Instagram
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Sistem Informasi
Depositing User: Sendi Ramadani
Date Deposited: 08 Aug 2024 06:14
Last Modified: 08 Aug 2024 06:14
URI: http://repository.wicida.ac.id/id/eprint/5698

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